An unsupervised approach for measuring myocardial perfusion in MR image sequences

Antoine Discher; Nicolas Rougon; Francoise Preteux

doi:10.1117/12.621358

30 August 2005 An unsupervised approach for measuring myocardial perfusion in MR image sequences

Antoine Discher, Nicolas Rougon, Francoise Preteux

Proceedings Volume 5916, Mathematical Methods in Pattern and Image Analysis; 59160C (2005) https://doi.org/10.1117/12.621358
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

Quantitatively assessing myocardial perfusion is a key issue for the diagnosis, therapeutic planning and patient follow-up of cardio-vascular diseases. To this end, perfusion MRI (p-MRI) has emerged as a valuable clinical investigation tool thanks to its ability of dynamically imaging the first pass of a contrast bolus in the framework of stress/rest exams. However, reliable techniques for automatically computing regional first pass curves from 2D short-axis cardiac p-MRI sequences remain to be elaborated. We address this problem and develop an unsupervised four-step approach comprising: (i) a coarse spatio-temporal segmentation step, allowing to automatically detect a region of interest for the heart over the whole sequence, and to select a reference frame with maximal myocardium contrast; (ii) a model-based variational segmentation step of the reference frame, yielding a bi-ventricular partition of the heart into left ventricle, right ventricle and myocardium components; (iii) a respiratory/cardiac motion artifacts compensation step using a novel region-driven intensity-based non rigid registration technique, allowing to elastically propagate the reference bi-ventricular segmentation over the whole sequence; (iv) a measurement step, delivering first-pass curves over each region of a segmental model of the myocardium. The performance of this approach is assessed over a database of 15 normal and pathological subjects, and compared with perfusion measurements delivered by a MRI manufacturer software package based on manual delineations by a medical expert.

Citation Download Citation

Antoine Discher, Nicolas Rougon, and Francoise Preteux "An unsupervised approach for measuring myocardial perfusion in MR image sequences", Proc. SPIE 5916, Mathematical Methods in Pattern and Image Analysis, 59160C (30 August 2005); https://doi.org/10.1117/12.621358

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available